def test_saveStandoffFile_fromSimpleTag():
text = 'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />'
corpus = kindred.Corpus()
doc = kindred.Document(text)
corpus.addDocument(doc)
tempDir = tempfile.mkdtemp()
kindred.save(corpus,'standoff',tempDir)
loadedCorpus = kindred.loadDir('standoff',tempDir)
assert isinstance(loadedCorpus,kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc,kindred.Document)
entities = loadedDoc.getEntities()
relations = loadedDoc.getRelations()
sourceEntityIDsToEntityIDs = loadedDoc.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],expectedType='disease',expectedText='colorectal cancer',expectedPos=[(4,21)],expectedSourceEntityID="T1")
assertEntity(entities[1],expectedType='gene',expectedText='APC',expectedPos=[(49,52)],expectedSourceEntityID="T2")
assert relations == [kindred.Relation('causes',[sourceEntityIDsToEntityIDs["T1"],sourceEntityIDsToEntityIDs["T2"]],['obj','subj'])], "(%s) not as expected" % relations
shutil.rmtree(tempDir)
def test_saveStandoffFile_SeparateSentences():
texts = ['The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />','<disease id="T1">Li-Fraumeni</disease> was caused by mutations in <gene id="T2">P53</gene><relation type="causes" subj="T2" obj="T1" />']
corpus = kindred.Corpus()
for t in texts:
doc = kindred.Document(t)
corpus.addDocument(doc)
tempDir = tempfile.mkdtemp()
kindred.save(corpus,'standoff',tempDir)
loadedCorpus = kindred.loadDir('standoff',tempDir)
assert isinstance(loadedCorpus,kindred.Corpus)
assert len(loadedCorpus.documents) == 2
data = loadedCorpus.documents[0]
assert isinstance(data,kindred.Document)
entities = data.getEntities()
relations = data.getRelations()
sourceEntityIDsToEntityIDs = data.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],expectedType='disease',expectedText='colorectal cancer',expectedPos=[(4,21)],expectedSourceEntityID="T1")
assertEntity(entities[1],expectedType='gene',expectedText='APC',expectedPos=[(49,52)],expectedSourceEntityID="T2")
assert relations == [kindred.Relation('causes',[sourceEntityIDsToEntityIDs["T1"],sourceEntityIDsToEntityIDs["T2"]],['obj','subj'])], "(%s) not as expected" % relations
data = loadedCorpus.documents[1]
assert isinstance(data,kindred.Document)
entities = data.getEntities()
relations = data.getRelations()
sourceEntityIDsToEntityIDs = data.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],expectedType='disease',expectedText='Li-Fraumeni',expectedPos=[(0,11)],expectedSourceEntityID="T1")
assertEntity(entities[1],expectedType='gene',expectedText='P53',expectedPos=[(39,42)],expectedSourceEntityID="T2")
assert relations == [kindred.Relation('causes',[sourceEntityIDsToEntityIDs["T1"],sourceEntityIDsToEntityIDs["T2"]],['obj','subj'])], "(%s) not as expected" % relations
shutil.rmtree(tempDir)
def test_saveStandoffFile_noArgNames():
text = "The colorectal cancer was caused by mutations in APC"
e1 = kindred.Entity(entityType="disease",text="colorectal cancer",position=[(4, 21)],sourceEntityID="T1")
e2 = kindred.Entity(entityType="gene",text="APC",position=[(49, 52)],sourceEntityID="T2")
rel = kindred.Relation(relationType="causes",entityIDs=[e1.entityID,e2.entityID])
doc = kindred.Document(text,[e1,e2],[rel],relationsUseSourceIDs=False)
corpus = kindred.Corpus()
corpus.addDocument(doc)
tempDir = tempfile.mkdtemp()
kindred.save(corpus,'standoff',tempDir)
loadedCorpus = kindred.loadDir('standoff',tempDir)
assert isinstance(loadedCorpus,kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc,kindred.Document)
entities = loadedDoc.getEntities()
relations = loadedDoc.getRelations()
sourceEntityIDsToEntityIDs = loadedDoc.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],expectedType='disease',expectedText='colorectal cancer',expectedPos=[(4,21)],expectedSourceEntityID="T1")
assertEntity(entities[1],expectedType='gene',expectedText='APC',expectedPos=[(49,52)],expectedSourceEntityID="T2")
assert relations == [kindred.Relation('causes',[sourceEntityIDsToEntityIDs["T1"],sourceEntityIDsToEntityIDs["T2"]],['arg1','arg2'])], "(%s) not as expected" % relations
shutil.rmtree(tempDir)
def test_iterLoadBiocFile():
text = 'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />'
corpus = kindred.Corpus(text,loadFromSimpleTag=True)
docsToCreate = 100
tempDir = tempfile.mkdtemp()
singleDoc = corpus.documents[0]
corpus.documents = [ singleDoc for _ in range(docsToCreate) ]
kindred.save(corpus,'bioc',tempDir)
biocPath = os.path.join(tempDir,'collection.bioc.xml')
totalDocCount = 0
for corpus in kindred.iterLoadDataFromBioc(biocPath,corpusSizeCutoff=3):
assert isinstance(corpus,kindred.Corpus)
assert len(corpus.documents) <= 25
totalDocCount += len(corpus.documents)
for doc in corpus.documents:
assert isinstance(doc,kindred.Document)
entities = doc.getEntities()
relations = doc.getRelations()
sourceEntityIDsToEntityIDs = doc.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],expectedType='disease',expectedText='colorectal cancer',expectedPos=[(4,21)],expectedSourceEntityID="T1")
assertEntity(entities[1],expectedType='gene',expectedText='APC',expectedPos=[(49,52)],expectedSourceEntityID="T2")
assert relations == [kindred.Relation('causes',[sourceEntityIDsToEntityIDs["T1"],sourceEntityIDsToEntityIDs["T2"]],['obj','subj'])], "(%s) not as expected" % relations
assert totalDocCount == docsToCreate
shutil.rmtree(tempDir)
def test_saveStandoffFile_noSourceEntityID():
text = 'The <disease>colorectal cancer</disease> is bad.'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
with TempDir() as tempDir:
with pytest.raises(AssertionError) as excinfo:
kindred.save(corpus, 'standoff', tempDir)
assert excinfo.value.args[
0] == 'Entities must have a sourceEntityID (e.g. T1) to be saved in the standoff format'
def test_saveStandoffFile():
text = "The colorectal cancer was caused by mutations in APC"
e1 = kindred.Entity(entityType="disease",
text="colorectal cancer",
position=[(4, 21)],
sourceEntityID="T1")
e2 = kindred.Entity(entityType="gene",
text="APC",
position=[(49, 52)],
sourceEntityID="T2")
rel = kindred.Relation(relationType="causes",
entities=[e1, e2],
argNames=['obj', 'subj'])
doc = kindred.Document(text, [e1, e2], [rel])
corpus = kindred.Corpus()
corpus.addDocument(doc)
with TempDir() as tempDir:
kindred.save(corpus, 'standoff', tempDir)
for filename in os.listdir(tempDir):
if filename.endswith('.a2'):
checkRelationAnnotations(os.path.join(tempDir, filename))
loadedCorpus = kindred.load('standoff', tempDir)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc, kindred.Document)
entities = loadedDoc.entities
relations = loadedDoc.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='colorectal cancer',
expectedPos=[(4, 21)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='APC',
expectedPos=[(49, 52)],
expectedSourceEntityID="T2")
assert relations == [
kindred.Relation(
'causes',
[sourceEntityIDToEntity["T1"], sourceEntityIDToEntity["T2"]],
['obj', 'subj'],
sourceRelationID='R1')
], "(%s) not as expected" % relations
def test_saveBB3Data():
corpus = kindred.bionlpst.load('2016-BB3-event-train')
assert isinstance(corpus,kindred.Corpus)
tempDir = tempfile.mkdtemp()
kindred.save(corpus,'standoff',tempDir)
loadedCorpus = kindred.loadDir('standoff',tempDir)
assert len(corpus.documents) == len(loadedCorpus.documents)
shutil.rmtree(tempDir)
def test_saveBB3Data():
corpus = kindred.bionlpst.load('2016-BB3-event-train')
assert isinstance(corpus, kindred.Corpus)
with TempDir() as tempDir:
kindred.save(corpus, 'standoff', tempDir)
for filename in os.listdir(tempDir):
if filename.endswith('.a2'):
checkRelationAnnotations(os.path.join(tempDir, filename))
loadedCorpus = kindred.load('standoff', tempDir)
assert len(corpus.documents) == len(loadedCorpus.documents)
def test_iterLoadBiocFile():
text = 'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
docsToCreate = 100
with TempDir() as tempDir:
singleDoc = corpus.documents[0]
corpus.documents = [singleDoc for _ in range(docsToCreate)]
tempFile = os.path.join(tempDir, 'corpus.bioc.xml')
kindred.save(corpus, 'biocxml', tempFile)
totalDocCount = 0
for corpus in kindred.iterLoad('biocxml', tempFile,
corpusSizeCutoff=3):
assert isinstance(corpus, kindred.Corpus)
assert len(corpus.documents) <= 25
totalDocCount += len(corpus.documents)
for doc in corpus.documents:
assert isinstance(doc, kindred.Document)
entities = doc.entities
relations = doc.relations
sourceEntityIDsToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='colorectal cancer',
expectedPos=[(4, 21)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='APC',
expectedPos=[(49, 52)],
expectedSourceEntityID="T2")
assert relations == [
kindred.Relation('causes', [
sourceEntityIDsToEntity["T1"],
sourceEntityIDsToEntity["T2"]
], ['obj', 'subj'])
], "(%s) not as expected" % relations
assert totalDocCount == docsToCreate
def test_saveStandoffFile_fromSimpleTag_triple():
text = '<drug id="T1">Erlotinib</drug>, a <gene id="T2">EGFR</gene> inhibitor is commonly used for <disease id="T3">NSCLC</disease> patients. <relation type="druginfo" drug="T1" gene="T2" disease="T3" />'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
with TempDir() as tempDir:
kindred.save(corpus, 'standoff', tempDir)
for filename in os.listdir(tempDir):
if filename.endswith('.a2'):
checkRelationAnnotations(os.path.join(tempDir, filename))
loadedCorpus = kindred.load('standoff', tempDir)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc, kindred.Document)
entities = loadedDoc.entities
relations = loadedDoc.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='drug',
expectedText='Erlotinib',
expectedPos=[(0, 9)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='EGFR',
expectedPos=[(13, 17)],
expectedSourceEntityID="T2")
assertEntity(entities[2],
expectedType='disease',
expectedText='NSCLC',
expectedPos=[(49, 54)],
expectedSourceEntityID="T3")
assert relations == [
kindred.Relation('druginfo', [
sourceEntityIDToEntity["T3"], sourceEntityIDToEntity["T1"],
sourceEntityIDToEntity["T2"]
], ['disease', 'drug', 'gene'],
sourceRelationID='R1')
], "(%s) not as expected" % relations
def test_saveStandoffFile_fromSimpleTag_binary():
text = 'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
with TempDir() as tempDir:
kindred.save(corpus, 'standoff', tempDir)
for filename in os.listdir(tempDir):
if filename.endswith('.a2'):
checkRelationAnnotations(os.path.join(tempDir, filename))
loadedCorpus = kindred.load('standoff', tempDir)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc, kindred.Document)
entities = loadedDoc.entities
relations = loadedDoc.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='colorectal cancer',
expectedPos=[(4, 21)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='APC',
expectedPos=[(49, 52)],
expectedSourceEntityID="T2")
print([r.sourceRelationID for r in relations])
assert relations == [
kindred.Relation(
'causes',
[sourceEntityIDToEntity["T1"], sourceEntityIDToEntity["T2"]],
['obj', 'subj'],
sourceRelationID='R1')
], "(%s) not as expected" % relations
def test_saveStandoffFile_fromSimpleTag_triple():
text = '<drug id="T1">Erlotinib</drug>, a <gene id="T2">EGFR</gene> inhibitor is commonly used for <disease id="T3">NSCLC</disease> patients. <relation type="druginfo" drug="T1" gene="T2" disease="T3" />'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
tempDir = tempfile.mkdtemp()
kindred.save(corpus, 'standoff', tempDir)
loadedCorpus = kindred.loadDir('standoff', tempDir)
shutil.rmtree(tempDir)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc, kindred.Document)
entities = loadedDoc.getEntities()
relations = loadedDoc.getRelations()
sourceEntityIDsToEntityIDs = loadedDoc.getSourceEntityIDsToEntityIDs()
assertEntity(entities[0],
expectedType='drug',
expectedText='Erlotinib',
expectedPos=[(0, 9)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='EGFR',
expectedPos=[(13, 17)],
expectedSourceEntityID="T2")
assertEntity(entities[2],
expectedType='disease',
expectedText='NSCLC',
expectedPos=[(49, 54)],
expectedSourceEntityID="T3")
assert relations == [
kindred.Relation('druginfo', [
sourceEntityIDsToEntityIDs["T3"], sourceEntityIDsToEntityIDs["T1"],
sourceEntityIDsToEntityIDs["T2"]
], ['disease', 'drug', 'gene'])
], "(%s) not as expected" % relations
def test_savePubAnnotationFile_fromSimpleTag():
text = 'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />'
corpus = kindred.Corpus(text, loadFromSimpleTag=True)
with TempDir() as tempDir:
tempFile = os.path.join(tempDir, 'corpus.json')
kindred.save(corpus, 'pubannotation', tempFile)
loadedCorpus = kindred.load('pubannotation', tempFile)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 1
loadedDoc = loadedCorpus.documents[0]
assert isinstance(loadedDoc, kindred.Document)
entities = loadedDoc.entities
relations = loadedDoc.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='colorectal cancer',
expectedPos=[(4, 21)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='APC',
expectedPos=[(49, 52)],
expectedSourceEntityID="T2")
print([r.sourceRelationID for r in relations])
assert relations == [
kindred.Relation(
'causes',
[sourceEntityIDToEntity["T1"], sourceEntityIDToEntity["T2"]],
['subj', 'obj'],
sourceRelationID='R1')
], "(%s) not as expected" % relations
def _bionlpst_seedev_testSet():
trainData = kindred.bionlpst.load('2016-SeeDev-binary-train')
devData = kindred.bionlpst.load('2016-SeeDev-binary-dev')
testData = kindred.bionlpst.load('2016-SeeDev-binary-test')
trainAndDevData = trainData + devData
print("Starting training...")
classifier = kindred.RelationClassifier()
classifier.train(trainAndDevData)
print("Predicting training...")
predictedRelations = classifier.predict(
testData) #devData_TextAndEntities)
print("Saving...")
outDir = 'out.SeeDev'
kindred.save(testData,
'standoff',
outDir,
predictedRelations=predictedRelations)
def _bionlpst_bb3_testSet():
trainData = kindred.bionlpst.load('2016-BB3-event-train')
devData = kindred.bionlpst.load('2016-BB3-event-dev')
testData = kindred.bionlpst.load('2016-BB3-event-test')
trainAndDevData = trainData + devData
print("Starting training...")
classifier = kindred.RelationClassifier(useBuilder=True)
#classifier = RelationClassifier(useBuilder=False)
classifier.train(trainAndDevData)
print("Predicting training...")
predictedRelations = classifier.predict(
testData) #devData_TextAndEntities)
print("Saving...")
outDir = 'out.BB3'
kindred.save(testData,
'standoff',
outDir,
predictedRelations=predictedRelations)
entityTypes = set([
entity.entityType
for entity, tokenIndices in sentence.entityAnnotations
])
entityInfo = [(e.entityType, e.text)
for e, tokenIndices in sentence.entityAnnotations
]
hasMutation = "Mutation" in entityTypes
hasChemical = "Chemical" in entityTypes
if hasMutation and hasChemical:
sentenceStart = sentence.tokens[0].startPos
sentenceEntities = [
kindred.Entity(e.entityType,
e.text,
[(e.position[0][0] - sentenceStart,
e.position[0][1] - sentenceStart)],
e.sourceEntityID,
e.externalID,
metadata=e.metadata)
for e, _ in sentence.entityAnnotations
]
newDoc = kindred.Document(sentence.text,
sentenceEntities,
metadata=doc.metadata)
sentenceCorpus.addDocument(newDoc)
kindred.save(sentenceCorpus, 'biocxml', args.outBioc)
import os
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Use annotated sentences to build a Kindred classifer and apply to unannotated sentences')
parser.add_argument('--dataToBuildModel',required=True,type=str,help='Sentences with relations')
parser.add_argument('--dataToApplyModel',required=True,type=str,help='Sentences without annotated relations to make predictions on')
parser.add_argument('--outDir',required=True,type=str,help='Directory to store output')
args = parser.parse_args()
print("Loading corpora...")
trainCorpus = kindred.load('standoff',args.dataToBuildModel)
predictionCorpus = kindred.load('standoff',args.dataToApplyModel)
print("Building classifier...")
classifier = kindred.RelationClassifier()
classifier.train(trainCorpus)
print("Applying classifier...")
classifier.predict(predictionCorpus)
if not os.path.isdir(args.outDir):
os.makedirs(args.outDir)
print("Saving results to directory...")
kindred.save(predictionCorpus,'standoff',args.outDir)
print("\nPredicted relations:")
for relation in predictionCorpus.getRelations():
print("%s\t%s" % (relation.entities[0].text,relation.entities[1].text))
sentenceCorpus = corpus.splitIntoSentences()
print("Looking for measurement words, e.g. voltage")
wordlist = {
('voltage', ): {('measurement', 'voltage')},
('current', ): {('measurement', 'current')}
}
entityRecognizer = kindred.EntityRecognizer(wordlist)
entityRecognizer.annotate(sentenceCorpus)
print("Looking for numeric values")
quantityRecognizer = QuantityRecognizer()
quantityRecognizer.annotate(sentenceCorpus)
print("Find every pair of a measurement word and a value")
candidateBuilder = kindred.CandidateBuilder(
acceptedEntityTypes=[('measurement', 'quantity')])
candidateRelations = candidateBuilder.build(sentenceCorpus)
print("Let's annotate a few")
withRelations, noRelations = kindred.manuallyAnnotate(
sentenceCorpus, candidateRelations)
outDir = 'numericalAnnotations'
if not os.path.isdir(outDir):
os.makedirs(outDir)
print("Saving results to directory...")
kindred.save(withRelations, 'standoff', outDir)
wordlistLookup = kindred.EntityRecognizer.loadWordlists(wordlistDict,
idColumn=0,
termsColumn=0)
print("Annotating entities in corpus with wordlists")
entityRecognizer = kindred.EntityRecognizer(wordlistLookup)
entityRecognizer.annotate(sentenceCorpus)
print("Finding all candidate relations")
acceptedEntityTypes = wordlistDict
candidateBuilder = kindred.CandidateBuilder(
entityCount=len(wordlistDict),
acceptedEntityTypes=[tuple(sorted(wordlistDict.keys()))])
candidateRelations = candidateBuilder.build(sentenceCorpus)
print(
"Time to through some of the candidate relations and annotate some...")
annotatedCorpus, unannotatedCorpus = kindred.manuallyAnnotate(
sentenceCorpus, candidateRelations)
print(
"\nSaving annotated corpus of %d sentences (with relations that you have just annotated)"
% len(annotatedCorpus.documents))
kindred.save(annotatedCorpus, 'standoff', annotatedDir)
print(
"Saving unannotated corpus of %d sentences (which you did not review)"
% len(unannotatedCorpus.documents))
kindred.save(unannotatedCorpus, 'standoff', unannotatedDir)
def test_saveStandoffFile_SeparateSentences():
texts = [
'The <disease id="T1">colorectal cancer</disease> was caused by mutations in <gene id="T2">APC</gene><relation type="causes" subj="T2" obj="T1" />',
'<disease id="T1">Li-Fraumeni</disease> was caused by mutations in <gene id="T2">P53</gene><relation type="causes" subj="T2" obj="T1" />'
]
corpus = kindred.Corpus()
for t in texts:
doc = kindred.Document(t, loadFromSimpleTag=True)
corpus.addDocument(doc)
with TempDir() as tempDir:
kindred.save(corpus, 'standoff', tempDir)
for filename in os.listdir(tempDir):
if filename.endswith('.a2'):
checkRelationAnnotations(os.path.join(tempDir, filename))
loadedCorpus = kindred.load('standoff', tempDir)
assert isinstance(loadedCorpus, kindred.Corpus)
assert len(loadedCorpus.documents) == 2
data = loadedCorpus.documents[0]
assert isinstance(data, kindred.Document)
entities = data.entities
relations = data.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='colorectal cancer',
expectedPos=[(4, 21)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='APC',
expectedPos=[(49, 52)],
expectedSourceEntityID="T2")
assert relations == [
kindred.Relation(
'causes',
[sourceEntityIDToEntity["T1"], sourceEntityIDToEntity["T2"]],
['obj', 'subj'])
], "(%s) not as expected" % relations
data = loadedCorpus.documents[1]
assert isinstance(data, kindred.Document)
entities = data.entities
relations = data.relations
sourceEntityIDToEntity = {
entity.sourceEntityID: entity
for entity in entities
}
assertEntity(entities[0],
expectedType='disease',
expectedText='Li-Fraumeni',
expectedPos=[(0, 11)],
expectedSourceEntityID="T1")
assertEntity(entities[1],
expectedType='gene',
expectedText='P53',
expectedPos=[(39, 42)],
expectedSourceEntityID="T2")
assert relations == [
kindred.Relation(
'causes',
[sourceEntityIDToEntity["T1"], sourceEntityIDToEntity["T2"]],
['obj', 'subj'])
], "(%s) not as expected" % relations
if not (e.entityType == 'Chemical'
and not e.metadata['conceptid'] in drugMeshIDs)
]
doc.entities = [
e for e in doc.entities
if not (e.entityType == 'Chemical' and len(e.text) <= 4)
]
doc.entities = [
e for e in doc.entities
if not (e.entityType == 'Mutation'
and pgmine.normalizeMutation(e.text) is None)
]
doc.entities = [
e for e in doc.entities
if not (e.entityType == 'Mutation'
and e.text.lower() in variantStopwords)
]
entityTypes = set(e.entityType for e in doc.entities)
if 'Chemical' in entityTypes and 'Mutation' in entityTypes:
filtered.append(doc)
corpus.documents += filtered
print("Found: ", len(corpus.documents))
corpus.documents = random.sample(corpus.documents, 500)
kindred.save(corpus, 'standoff', args.outDir)
kindred.save(corpus, 'biocxml', os.path.join(args.outDir,
'corpus.bioc.xml'))
